neural-dialogue-metrics/EmbeddingBased
Embedding-based evaluation metrics for dialogue generation.
This tool helps evaluate the quality of responses generated by dialogue systems. It takes a file of human-written 'ground truth' dialogue responses and a file of predicted responses from an AI system. It then provides scores indicating how semantically similar the generated responses are to the ideal ones. Dialogue system developers and researchers would use this to gauge their model's performance.
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Use this if you are developing or researching AI dialogue systems and need an automated way to measure the semantic similarity of your system's output against human benchmarks.
Not ideal if you are looking for qualitative feedback on dialogue flow, coherence, or other human-like conversational aspects beyond semantic similarity.
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15
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Language
Python
License
MIT
Category
Last pushed
Jan 08, 2023
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0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/neural-dialogue-metrics/EmbeddingBased"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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